A MATLAB-based app to improve LC-MS/MS data analysis for N-linked glycan peak identification

Area of Science:

• Biochemistry
• Analytical Chemistry
• Bioinformatics

Background:

• Glycosylation is a critical protein modification influencing biological processes.
• Manual analysis of glycan structures via LC/MS and MS/MS is time-consuming and complex.
• Existing glycobioinformatics tools are often costly or academic-focused, hindering industrial high-throughput applications.

Purpose of the Study:

• To develop an automated, user-friendly software tool for glycan analysis in biopharmaceutical settings.
• To streamline the processing, identification, and reporting of glycan structures from LC/MS data.
• To provide a cost-effective and adaptable solution for standardized glycan analysis.

Main Methods:

• Development of a MATLAB-based application, GlyKAn AZ, with a graphical user interface (GUI).
• Implementation of MS1 and MS2 mass search algorithms and glycan databases for glycan species confirmation.
• Inclusion of a Fragment Generator for expanding glycan databases and automatic MS/MS spectra annotation.

Main Results:

• GlyKAn AZ automates glycan identification and data processing in a streamlined workflow.
• The app features customizable displays and generates report-ready annotated MS/MS spectra.
• Validation confirmed the accurate identification of all glycan species, comparable to manual analysis.

Conclusions:

• GlyKAn AZ expedites glycan analysis with high accuracy, improving manual workflows.
• The app's customizable features and outputs benefit both academic and industrial research.
• It provides a valuable tool for efficient and standardized glycan identification.